Predict models for prolonged ICU stay using APACHE II, APACHE III and SAPS II scores: A Japanese multicenter retrospective cohort study

Prolonged ICU stays are associated with high costs and increased mortality. Thus, early prediction of such stays would help clinicians to plan initial interventions, which could lead to efficient utilization of ICU resources. The aim of this study was to develop models for predicting prolonged stays in Japanese ICUs using APACHE II, APACHE III and SAPS II scores. In this multicenter retrospective cohort study, we analyzed the cases of 85,558 patients registered in the Japanese Intensive care Patient Database between 2015 and 2019. Prolonged ICU stay was defined as an ICU stay of >14 days. Multivariable logistic regression analyses were performed to develop three predictive models for prolonged ICU stay using APACHE II, APACHE III and SAPS II scores, respectively. After exclusions, 79,620 patients were analyzed, 2,364 of whom (2.97%) experienced prolonged ICU stays. Multivariable logistic regression analyses showed that severity scores, BMI, MET/RRT, postresuscitation, readmission, length of stay before ICU admission, and diagnosis at ICU admission were significantly associated with higher risk of prolonged ICU stay in all models. The present study developed predictive models for prolonged ICU stay using severity scores. These models may be helpful for efficient utilization of ICU resources.


Introduction
Length of stay (LOS) in the intensive care unit (ICU) is an indicator of the efficiency of intensive care, because it is associated with both the costs of intensive care and ICU resource utilization [1,2]. Because ICU resources are limited but the demands have recently increased, we considered that an examination of LOS in the ICU could lead to improvements in the efficiency of intensive care. medical emergency team (RRT/MET), post resuscitation, emergency admission, type of admission (non-operation, elective surgery, or emergency surgery), and readmission], chronic co-morbidity [acquired immunodeficiency syndrome (AIDS), heart failure, respiratory failure, hepatic insufficiency, cirrhosis, acute myeloid leukemia/multiple myeloma, lymphoma, cancer metastasis, hemodialysis, and immunosuppression], LOS before ICU admission, diagnosis at ICU admission, APACHE II, APACHE III and SAPS II scores, acute kidney injury in the first 24 h after ICU admission, mechanical ventilation in the first 24 h after ICU admission, treatment in the ICU [intra-aortic balloon pumping, veno-venous extracorporeal membrane oxygenation, percutaneous cardiopulmonary support, intermittent renal replacement therapy, continuous renal replacement therapy, and plasma exchange], and outcome (LOS in the ICU, LOS in the hospital, ICU death, and hospital death). Definitions of chronic co-morbidity were based on that of APACHE II, APACHE III and/or SAPS II scores.

Statistical analyses
Patient's characteristic data are presented as the median (25th to 75th percentile) and the number (a percentage of each group). Statistical differences between the study groups were assessed using Chi-squared test for categorical variables and Mann-Whitney U test for continuous variables.
Multivariable logistic regression analyses were performed to develop predictive models for prolonged ICU stay using the APACHE II, APACHE III and SAPS II scores (Models 1-3). Models 1, 2, and 3 included APACHE II, APACHE III and SAPS II scores, respectively. These scores were split into multiple categories: for the APACHE II score, the categories were -10, 11-20, 21-30, 31-40, and 41+; for the APACHE III score, they were -40, 41-80, 81-120, 121-160, and 161+; and for the SAPS II score, they were -25, 25-50, 51-75, 76-100, and 101+. In addition to gender and BMI, readmission, type of admission, LOS before ICU admission, and diagnosis at ICU admission were included to adjust the patient characteristics in these models, because these variables were reported to be associated with prolonged ICU stay [2,[14][15][16]. RRT/MET and post resuscitation were also included, because these were associated with emergency admission or surgery, which is reported to be a risk factor for prolonged ICU stay [2,16]. Several factors that are used for the calculation of these scores or associated with these scores, such as age, type of admission, and chronic disease, were not included. Because there were no patients with post-operative hematological disease in group P, post-operative hematological disease was combined with post-operative metabolic disease in these models. Variance inflation factor (VIF) was used to check for multicollinearity among the variables. VIF >10 indicates the presence of multicollinearity, which requires correction of variable selection. Discrimination was measured using the area under the curve (AUC). The results are expressed as adjusted odds ratios (aORs) with corresponding 95% confidence intervals (CIs).
Moreover, multivariable logistic regression analyses were conducted to evaluate whether prolonged ICU stay is associated with hospital mortality among ICU survivors. The APACHE II, APACHE III and SAPS II scores were included in the respective model to adjust for the disease severity of the patient.
In the present study, we used all available data in the JIPAD database in order to maximize the power and generalizability of the results.
All data analyses were performed with EZR software ver. 1.37 (Saitama Medical Center, Jichi Medical University, Saitama, Japan). P-values<0.05 were considered significant in all tests.
This manuscript adheres to the applicable TRIPOD guideline [17].

Characteristics of patients
Of the 85,558 patients, 79,620 patients were finally analyzed after the above-described exclusions (Fig 1). Of the 79,620 patients, 77,256 and 2,364 patients were assigned to groups NP and P, respectively. The prevalence of prolonged ICU stay was 2.97%. The patient characteristics are shown in Tables 1-4 (Fig 2). Severity scores and prolonged ICU stay APACHE II, APACHE III and SAPS II scores were significantly higher in group P than in group NP ( Table 4). The results of multivariable logistic regression analyses to develop predictive models for prolonged ICU stay using the APACHE II, APACHE III and SAPS II scores are shown in Table 5. ROC curves for each predictive model are shown in Fig 4. When the type of admission was included in these models, the VIF values of it and diagnosis were more than 10 in all models. Thus, the type of admission was not included. In these models, there were no VIF values of 10 or higher, indicating that there was no collinearity.

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disease, post-operative urinary disease, post-operative muscle/bone/skin disease, post-operative obstetrics/gynecological disease, and non-operative metabolic disease) were significantly associated with lower risk of prolonged ICU stay (

Prolonged ICU stay and hospital mortality
Hospital mortality of group P was significantly higher than that of group NP (7.2% vs. 39.2%, p<0.001) ( Table 1). Multivariable logistic regression analyses showed that prolonged ICU stay was significantly associated with an increased hospital mortality after adjusting for the severity scores ( Table 6, Models 1-3). ROC curves for each model are shown in Fig 4. The aORs for hospital mortality increased as the LOS in the ICU increased except 0 day LOS.

Discussion
The present study developed a predictive model for prolonged ICU stay using APACHE II, APACHE III and SAPS II scores. In addition to each severity score, BMI (category: 25-35 kg/ m 2 ), MET/RRT, post resuscitation, readmission, LOS before ICU admission (category: 15 + days), and diagnosis (categories: non-operative respiratory disease, non-operative neurological disease, non-operative trauma, and non-operative muscle/bone/skin disease) were significantly associated with higher risk of prolonged ICU stay in all models. The AUC values for all logistic regression models were more than 0.8, which means that the discrimination abilities of these models were good. Moreover, prolonged ICU stay was significantly associated with an increased hospital mortality.
The present study showed that the prevalence of prolonged ICU stay was 2.97% in Japan. On the other hand, previous studies showed that the prevalence was 4-11% [2,14,15], even though these studies defined a prolonged ICU stay as >14 days just as in the present study. The prevalence of prolonged ICU stay in the present study was the lowest of these four studies. This might be due to the differences in patients' severity and type of admission among the studies. Whereas the mean (±standard deviation) APACHE II score was 15 [2,14,15]. Moreover, the proportion of admission to the ICU after elective surgery was 60.4% in the present study, which was higher than those in the other studies. As mentioned in the materials and methods section, in the Japanese health insurance system, special fees for critical care are limited to a period of 14 days, even if the status of the patient remains serious for more than 14 days. Thus, the rules of the Japanese health insurance system might affect the prevalence of prolonged ICU stay in Japan.
To the best of our knowledge, this is the first study to develop models for predicting prolonged ICU stays in Japan. We adjusted the disease severity of patient's using the APACHE and SAPS scores. These scores have been reported to be significant predictors for LOS in the ICU [9,10,16,18,19]. For purposes of the present analysis, we divided each severity score into five categories. Four of the categories were significantly associated with a higher risk of prolonged ICU stay compared to the lowest category. Although the aORs increased as the severity score category increased up to the 4th category, the aORs decreased in the highest (5th) category compared to the 4th category. This was due to the fact that patients with extremely severe disease are likely to die early in their ICU stay, and thus their LOS in the ICU tends to be short [20,21]. Similarly, BMI of 25-35 kg/m 2 was associated with a higher risk of prolonged ICU stay, but BMI of 35+ kg/m 2 was not. Readmisson and an LOS before ICU admission of 15 + days were significantly associated with higher risk of prolonged ICU stay in the present study, which is consistent with previous studies [2,15,20]. Although our PubMed search did not uncover any studies that described the relationship between prolonged ICU stay and either RRT/MET or post resuscitation, two studies showed that emergency admission and surgery were significantly associated with higher risk of prolonged ICU stay [2,20]. We did not include them in our models, because they are used for calculation of severity scores or are associated with these scores. Regarding diagnosis at ICU admission, previous studies reported that nonoperative respiratory disease, non-operative/post-operative trauma and non-operative neurological disease were significantly associated with higher risk of prolonged ICU stay [2,16]. In addition, the present study showed that non-operative muscle/bone/skin disease were significantly associated with higher risk of prolonged ICU stay. These models may be useful for helping clinicians to identify patients who are likely to have a prolonged ICU stay, and thereby for helping clinicians to control the allocation of ICU beds for effective resource utilization. In addition, this result may be used to calculate claimable special fees for critical care after 14 days in Japan to better reflect the disease severity of the patient compared to the present health insurance system. This study also showed that prolonged ICU stay was significantly associated with increased hospital mortality. This result was consistent with a previous retrospective cohort study which reported that 1-year mortality increased with increasing LOS in the ICU, and a clear LOS cutoff at which mortality rates significantly change was not found [5]. On the other hand, a retrospective cohort study demonstrated that LOS in the ICU was not significantly associated with a higher risk of hospital mortality [22]. This was likely to be due to the difference in definition

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of prolonged ICU stay. In the study by Williams et al., a prolonged ICU stay was defined as >10 days [22]. Another study reported that mortality increased with LOS in the ICU up to 10 days, but remained stable thereafter [23]. Thus, because the association between prolonged ICU stay and mortality remains controversial, multi-center prospective cohort studies are warranted to address this topic.
The present study has several limitations. First, as this was a retrospective observational study, there might be undetected confounding factors that affected the results. Second, as we used a Japanese national database, possible ethnic and medical system differences should be considered. Third, as patients were not followed after discharge from the hospital, we could not evaluate 1-year mortality or long-term outcomes.

Conclusions
The present study developed predictive models for prolonged ICU stay using the APACHE II, APACHE III and SAPS II scores. In addition, prolonged ICU stay was significantly associated with an increased hospital mortality. These findings may be helpful for the efficient utilization of ICU resources.